High utility itemset mining using path encoding and constrained subset generation

In this paper a two phase approach for high utility itemset mining has been proposed. In the first phase potential high utility itemsets are generated using potential high utility maximal supersets. The transaction weighted utility measure is used in ascertaining the potential high utility itemsets. The maximal supersets are obtained from high utility paths ending in the items in the transaction database. The supersets are constructed without using any tree structures. The prefix information of an item in a transaction is stored in the form of binary codes. Thus, the prefix information of a path in a transaction is encoded as binary codes and stored in the node containing the item information. The potential high utility itemsets are generated from the maximal supersets using a modified set enumeration tree. The high utility itemsets are then obtained from the set enumeration tree by calculating the actual utility by scanning the transaction database. The experiments highlight the superior performance of the system compared to other similar systems in the literature.